1. Field of the Invention
This invention pertains generally image detection, and more particularly to detection of man-made devices within the body of a patient.
2. Description of Related Art
Numerous systems have been developed for recognizing man-made devices (buildings, planes, cars, etc) in non-medical images (digital photographs, satellite images, etc). While computer-aided detection (CAD) systems have been developed for detecting and measuring organs and diseases in medical images, CAD has been traditionally only designed for oncology tasks to aid physicians in identifying subtle nodules, lesions etc. However CAD holds much promise in aiding radiologists in routine clinical tasks.
Currently, the presence and location of implantable man-made devices (IMD's) in medical images are assessed visually by a radiologist. The use of computer aided detection would substantially reduce the cost of this frequently performed radiologic interpretation.
Chest radiographs are used to confirm placement of life support tubes in patients, and incorrect placement of these tube can cause severe complications and can even be fatal. Incorrect placements of the Endotracheal (ET) tube typically include the tube being placed in the esophagus or in the soft tissue of the neck. Incorrect placement of the Nasogastric (NG) tube, for example, in the pleural cavity can cause pneumothorax. Accordingly, detecting tube placement is critical for patients in ICU's as incorrect tube placements can cause serious complications and can even be life threatening.
Assessing tube placement on chest radiographs is a difficult, time consuming task for radiologists and ICU personnel given the high volume of cases and the need for rapid interpretation. Chest radiographs are the quickest and safest method to check placement of these tubes. Tertiary ICU's typically generate hundreds of chest radiographs per day to confirm tube placement in patients. Radiographs of patients in ICU's are often cluttered with different tubes providing life support and wires monitoring the patient vital signs some outside and some inside the body. This makes the task of identifying these tubes a difficult and time consuming process for radiologists.
There has been very little research on detecting catheters, tubes and wires in chest radiographs, despite the significant clinical need.
Accordingly, an objective of the present invention is a system and methods to automatically detect and classify catheters with minimal change to the radiology workflow.